Mapping Distinct Forest Types Improves Overall Forest Identification Based on Multi-Spectral Landsat Imagery for Myanmar’s Tanintharyi Region

Abstract

Abstract:We investigated the use of multi-spectral Landsat OLI imagery for delineating mangrove, lowland evergreen, upland evergreen and mixed deciduous forest types in Myanmar's Tanintharyi Region and estimated the extent of degraded forest for each unique forest type. We mapped a total of 16 natural and human land use classes using both a Random Forest algorithm and a multivariate Gaussian model while considering scenarios with all natural forest classes grouped into a single intact or degraded category. Overall, classification accuracy increased for the multivariate Gaussian model with the partitioning of intact and degraded forest into separate forest cover classes but slightly decreased based on the Random Forest classifier. Natural forest cover was estimated to be 80.7% of total area in Tanintharyi. The most prevalent forest types are upland evergreen forest (42.3% of area) and lowland evergreen forest (21.6%). However, while just 27.1% of upland evergreen forest was classified as degraded (on the basis of canopy cover <80%), 66.0% of mangrove forest and 47.5% of the region's biologically-rich lowland evergreen forest were classified as degraded. This information on the current status of Tanintharyi's unique forest ecosystems and patterns of human land use is critical to effective conservation strategies and land-use planning.

Rapid forest clearing in a Myanmar proposed national park threatens two newly discovered species of geckos (Gekkonidae: Cyrtodactylus)

“…The estimated extent of forest loss in this study largely agrees with a March 2016 land cover analysis for Tanintharyi that focused on mapping the region’s unique forest types and areas of forest degradation [24]. Within the proposed protected areas and surrounding 10 km buffer, just 8.6% of the area identified as deforested in the current study was classified as intact forest in the previous study.…”

Assessing environmental impacts and change in Myanmar's mangrove ecosystem service value due to deforestation (2000–2014)

“…For instance, while our 2014 mangrove forest cover estimate for Tanintharyi (0.24 million ha) and the estimate of Gaw, Linkie, and Friess () for the same state and year were relatively close (0.25 million ha), this was not necessarily the case for the year 2000 (0.28 and 0.26 million ha, respectively). For the years 2015 and 2016, De Alban, Connette, Oswald, and Webb () and Connette, Oswald, Songer, and Leimgruber () estimated the state's mangrove area to be 0.34 and 0.24 million ha, respectively. Furthermore, Weber, Keddell, and Kemal () estimated a 0.03 million ha net mangrove forest cover loss from 2000 to 2013 in Rakhine state, whereas in this study, we detected a 0.08 million ha net mangrove forest cover loss from 2000 to 2014 (Table ).…”

Mangrove forest dynamics in Tanintharyi, Myanmar from 1989–2014, and the role of future economic and political developments

“…Connette et al . () report that 39.9 per cent of mangroves in the region are under protection and business as usual scenarios suggest that unprotected forest will remain even beyond the year 2100. However, such trends belie two important points.…”

“…If planned correctly and within a clear governance framework, ongoing political and economic reforms have the opportunity to improve mangrove management and rehabilitation by reforming complex natural resource governance arrangements and providing opportunities for novel public‐private financing and management of mangrove resources (Friess et al ., ). This will require the better protection and governance of mangrove forests, as currently less than 40 per cent of Tanintharyi's mangroves are legally protected (Connette et al, ).…”